1. Field of the Invention
The invention pertains generally to a system and method for remote detection and warning of hazardous vapors and aerosols and in particular to a system and method for imaging hazardous clouds.
2. Description of Related Art
There are military requirements for the remote detection and warning of chemical warfare vapors and aerosols and a developing civilian need for warning when there is a catastrophic release of a highly toxic compound such as occurred in Bhopal, India. Moreover, there is a general requirement for effective monitoring of chemical clouds, for example, for environmental protection and other reasons. The basic requirement is for warning, i.e., a system that senses and makes a decision without human intervention. Hazardous clouds are amorphous; consequently, the detection and warning systems of the prior art are generally based on spectral characteristics by which it is possible to differentiate between hazardous and non-hazardous clouds. The most developed of the remote sensing passive infrared systems make their decisions based on the integrated energy in a single field-of-view (FOV); i.e., they do not provide an image for interpretation by an operator.
Highly developed passive infrared imaging systems are generally known by the acronym FLIR (Forward Looking Infrared). Thermal infrared FLIR was first demonstrated in the early 1970's. These systems were originally developed for military needs but also have many civilian uses. FLIR's are capable of producing images of many intruder clouds; however, the image is difficult for operators to see when the background is complex or the cloud is larger than the FOV. Even when the cloud is detected, it has proved to be very difficult for the operator to differentiate between threat-simulant clouds and common interferents such as road dust and military screening smokes.
The only operational FLIR for the detection of chemical agents is the Navy's AN/KAS-1, which uses a conventional FLIR modified by the insertion of operator-selectable optical filters to enhance the image contrast for selected compounds such as Sarin. For Army or chemical plant operations, the difficulties of such an approach include: 1) a relatively small FOV, so that the operator must actively search to detect the cloud (a difficult operation in a complex environment unless the operator sees the cloud near its point of origin and can link it with the disseminating source); 2) a very limited capability for the operator to discriminate between chemical hazards and interferents with close spectral signatures, e.g., Sarin and kaolin dust; 3) a limitation to very few similar threats that are spectrally similar; and 4) no automatic capability; the operator must be in the loop at all times.
Conventional passive infrared spectroscopy for the remote detection of chemical agents was first proposed in the 1950's. It was recently brought to fruition with the type classification of the U.S. Army's M21. The M21 uses a conventional Fourier transform infrared (FTIR) sensor to produce a spectrum from which a decision is made on the presence or absence of a chemical agent cloud. In passive infrared spectroscopy, all useful information is contained in a small difference spectrum between the "clean" reference spectrum and the contaminated spectrum.
The M21 uses a conventional procedure to establish a difference spectrum based on measuring and recording a reference spectrum in an assumed clean environment and recursively updating it. The problem has been finding a recursive weight that does not have either too many false alarms or too few detections. (Other suggestions have included the operator swiveling the sensor to an area assumed to be clean and measuring a reference spectrum). The M21 scans seven separate, discontinuous FOV's (each of 1.5.degree. by 1.5.degree. separated by 10.degree. center to center), but does not produce an image. There are several proposed FTIR concepts that use arrays of detectors in the image plane of the interferometer, but these produce relatively conventionally sized images that are insufficiently large to form an image of a realistic threat cloud and/or insufficient etendue (throughput limited by the detector, the interferometer, the collector or the cloud size) for good sensitivity.
Many attempts have been made to bridge the gap between spectral and imaging systems. Traditional solutions generally insert optical filters into FLIR systems to enhance spectral discrimination. More recently, the single detector in the FTIR sensor has been replaced by a square array of detectors to enhance imaging capability. These solutions have had limited success because the sensors were optimized for different objectives with different constraints.
Passive spectroradiometers operate from a temperature difference, .DELTA.T, between the target cloud and the background. Natural temperature differences are generally very small, from a fraction of a .degree.K to a few .degree.K; therefore, achieving optimum performance is a very demanding problem. Sensitivity, i.e., the detection of minimum quantities, is a function of spectral resolution and scan time, it can be increased by either decreasing the spectral resolution and/or increasing the scan time. However, there are negative aspects to both of these approaches. With decreased spectral resolution there are increased problems of discrimination between target materials and interferents. With increased scan time there is less warning time. Resolution and scan time for automatic warning systems, such as the Army's M21, are generally fixed at the time of the design.
Conventional passive infrared detection and warning systems fix the resolution of the sensor and scan time at a value appropriate for laboratory analysis. This compromises both sensitivity and discrimination, i.e., the ability to differentiate between chemical agents. Differential signatures are formed by subtracting an internal infrared source (which does not maximize the signature of the threat) from the incoming signature or by subtracting a reference signature, measured at some earlier time at the same spatial position, from the incoming signature (which limits real time and mobile operation). A single resolution linear discriminant is used for both detection and discrimination.
Conventional methods of spectral detection and discrimination rely on a single linear discriminant applied to the difference spectrum. (This is an operation that is much more effectively done by a machine.) Sensitivity and discrimination are critically dependent on spectral resolution in an inverse way. The M21 is limited in sensitivity by its choice of a single conventional resolution of 4 cm.sup.-1, far higher than necessary for the detection of chemical agents.
The "fitting" of linear discriminants to the problem of detection and discrimination can be accomplished by many techniques; however, the various methods do not necessarily lead to the same result. Conventional methods of computing linear discriminants rely for the most part on "training" techniques ranging from linear regression to neural networks. Such training methods are very time-consuming and do not necessarily converge to a solution guaranteed to classify even known interferents properly; results depend not only on the training program, but also on how often the data are presented to the training program.